A novel hybrid methodology for short-term wind power forecasting based on adaptive neuro-fuzzy inference system

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• 作者：Jinqiang Liu ; Xiaoru Wang ; ^{xrwang@home.swjtu.edu.cn} ; Yun Lu
• 关键词：Short-term wind power forecasting ; Pearson correlation coefficient ; Neural network ; Least squares support vector machine ; Adaptive neuro-fuzzy inference system ; Hybrid methodology
• 刊名：Renewable Energy
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：103
• 期：Complete
• 页码：620-629
• 全文大小：3912 K
• 卷排序：103

文摘

Three individual intelligence models are used for short-term wind forecasting. A new data preprocess method based on Pearson correlation coefficients is proposed. A hybrid methodology based on adaptive neuro-fuzzy inference system is proposed. The proposed data preprocess method is prove to be effective. The proposed hybrid methodology presents a significant improvement in accuracy.